Beyond autocomplete - how AI is reshaping developer roles, teams, and the 'context tax'
For years, the enterprise conversation about Artificial Intelligence (AI) in the Software Development Lifecycle (SDLC) has been overly fixated on one metric - velocity.
With nearly 97% of developers now using AI tools in some capacity, the adoption phase is over. Enterprises have put AI coding assistants into their engineers’ hands.
But beyond the initial hype, Chief Information Officers (CIOs) and Chief Technology Officers (CTOs) are confronting a harder truth — code can be generated faster than ever, but software isn’t shipping any faster.
The bottleneck has moved. Modern software engineering rarely stalls on the mechanics of writing syntax. Instead, it stalls at the human stage, when workers ensure the code matches business intent. When AI tools operate in silos, they generate code untethered from requirements, user stories, and operational history. That’s hardly revolutionary.
To unlock real return on investment (ROI), enterprises must stop treating AI as an isolated...
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